Static deformation modulus is recognized as one of the most important parameters governing the behavior of rock masses. Predictive models for the mechanical properties of rock masses have been used in rock engineering because direct measurement of the properties is difficult due to time and cost constraints. In this method the deformation modulus is estimated indirectly from classification syst...

This paper describes a style adaptation technique using hidden semi-Markov model (HSMM) based maximum likelihood linear regression (MLLR). The HSMM-based MLLR technique can estimate regression matrices for affine transform of mean vectors of output and state duration distributions which maximize likelihood of adaptation data using EM algorithm. In this study, we apply this adaptation technique ...

Regression testing is the most expensive technique, but this technique gives confidence that whatever changes has been incorporated they are not making any adverse affect to the output. In Regression Test Selection Technique (RTST), we select test case from existing test set and perform test to validate modify the software. In this framework, it has been tried to reduce costs by selecting and r...

A novel semi-blind defocused image deconvolution technique is proposed, which is based on multivariate local polynomial regression and iterative Wiener filtering. In this technique, firstly a multivariate local polynomial regression model is trained in wavelet domain to estimate defocus parameter. After obtaining the point spread function (PSF ) parameter, iterative wiener filter is adopted to ...

static deformation modulus is recognized as one of the most important parameters governing the behavior of rock masses. predictive models for the mechanical properties of rock masses have been used in rock engineering because direct measurement of the properties is difficult due to time and cost constraints. in this method the deformation modulus is estimated indirectly from classification syst...

Regression testing is an expensive but necessary maintenance activity performed on modiied software to provide conndence that changes are correct and do not adversely aaect other portions of the software. A regression test selection technique chooses, from an existing test set, tests that are deemed necessary to validate modiied software. We present a new technique for regression test selection...

Regression testing is an important activity at both testing and maintenance phases. When a piece of software is modified, it is necessary to ensure the quality of the software is preserved. To this end, regression testing is to retest the software using the test cases selected from the original test pool. In this paper, we present a regression testing technique that selects test cases by utiliz...

this paper deals with ridge estimation of fuzzy nonparametric regression models using triangular fuzzy numbers. this estimation method is obtained by implementing ridge regression learning algorithm in the la- grangian dual space. the distance measure for fuzzy numbers that suggested by diamond is used and the local linear smoothing technique with the cross- validation procedure for selecting t...